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Theses/Dissertations

Statistics and Probability

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Experimental design

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Full-Text Articles in Physical Sciences and Mathematics

Data Analysis Using Experimental Design Model Factorial Analysis Of Variance/Covariance (Dmaovc.Bas), Wesley E. Newton May 1985

Data Analysis Using Experimental Design Model Factorial Analysis Of Variance/Covariance (Dmaovc.Bas), Wesley E. Newton

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

DMAOVC.BAS is a computer program written in the compiler version of microsoft basic which performs factorial analysis of variance/covariance with expected mean squares. The program accommodates factorial and other hierarchical experimental designs with balanced sets of data. The program is writ ten for use on most modest sized microprocessors, in which the compiler is available. The program is parameter file driven where the parameter file consists of the response variable structure, the experimental design model expressed in a similar structure as seen in most textbooks, information concerning the factors (i.e. fixed or random, and the number of levels), and necessary …


Fortran Programs For The Calculation Of Most Of The Commonly Used Experimental Design Models, H. Wain Greenhalgh May 1967

Fortran Programs For The Calculation Of Most Of The Commonly Used Experimental Design Models, H. Wain Greenhalgh

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Two computer programs were developed using a CDC 3100. They were written in FORTRAN IV.

One program uses four tape drives, one card reader, and one printer. It will calculate factorial analysis of variance with or without covariance and/or multivariate analysis for one to eight factors and up to twenty-five variables.

The other program is used for completely randomized designs, randomized block designs, and latin square designs. It will handle twenty-five treatments, rows (blocks), and columns. The program can handle fifteen variables using any number of these variables for covariates.